INTRODUCTION: Artificial light at night (ALAN) can disrupt circadian rhythms and cause sleep disturbances. Several previous epidemiological studies have reported an association between higher levels of outdoor ALAN and shorter sleep duration. However, it remains unclear how this association may differ by individual- and neighborhood-level socioeconomic status, and whether ALAN may also be associated with longer sleep duration. METHODS: We assessed the cross-sectional relationship between outdoor ALAN and self-reported sleep duration in 333,365 middle- to older-aged men and women in the NIH-AARP Diet and Health Study. Study participants reported baseline addresses, which were geocoded and linked with outdoor ALAN exposure measured by satellite imagery data obtained from the U.S. Defense Meteorological Satellite Program's Operational Linescan System. We used multinomial logistic regression to estimate the multinomial odds ratio (MOR) and 95% confidence intervals (CI) for the likelihood of reporting very short (<5h), short (<7h) and long (>/=9h) sleep relative to reporting 7-8h of sleep across quintiles of LAN. We also conducted subgroup analyses by individual-level education and census tract-level poverty levels. RESULTS: We found that higher levels of ALAN were associated with both very short and short sleep. When compared to the lowest quintile, the highest quintile of ALAN was associated with 16% and 25% increases in the likelihood of reporting short sleep in women (MORQ1 vs Q5, (95% CI), 1.16 (1.10, 1.22)) and men (1.25 (1.19, 1.31)), respectively. Moreover, we found that higher ALAN was associated with a decrease in the likelihood of reporting long sleep in men (0.79 (0.71, 0.89)). We also found that the associations between ALAN and short sleep were larger in neighborhoods with higher levels of poverty. CONCLUSIONS: The burden of short sleep may be higher among residents in areas with higher levels of outdoor LAN, and this association is likely stronger in poorer neighborhoods. Future studies should investigate the potential benefits of reducing light intensity in high ALAN areas in improve sleep health.

The landscape of fear has profound effects on the species behavior, with most organisms engaging in risk avoidance behaviors in areas perceived as riskier. Most risk avoidance behaviors, such as temporal avoidance, have severe trade-offs between foraging efficiency and risk reduction. Human activities are able to affect the species landscape of fear, by increasing mortality of individuals (i.e. hunting, roadkill) and by disruption of the clues used by the species to estimate predation risk (e.g. light pollution). In this study, we used an extensive camera-trapping and night-time light satellite imagery to evaluate whether human activities affect the diel activity patterns of 17 species of rainforest dwelling mammals. We found evidence of diel activity shifts in eight of 17 analyzed species, in which five species become 21.6 % more nocturnal and three species become 11.7% more diurnal in high disturbed areas. This activity shifts were observed for both diurnal and nocturnal species. Persecuted species (game and predators) were more susceptible to present activity shifts. Since changes in foraging activity may affect species fitness, the behavior of humans’ avoidance may be another driver of the Anthropocene defaunation.

Scattering by aerosols and gases cause a certain fraction of artificial light emitted upwards is redirected to the ground. Of all atmospheric constituents just the aerosols are most important modulators of night-sky brightness under cloudless conditions. Unlike most of the previous we highlight a crucial role of solar radiometry for determining the atmospheric optical depth before night-time observation is to be made. Aerosol optical depth at visible wavelengths extracted from the data measured provides then the information on size distribution or mean refractive index of aerosol particles that in turn are both necessary to make night sky brightness prediction more accurate. Therefore, combining daytime and night-time radiometry we can achieve accuracy much higher than ever before. This is due to significantly reduced uncertainty in aerosol properties.

The aerosol data are retrieved from a new portable multi-wavelength optical analyzer that operates Ocean Optics spectrometer. The equipment provides the radiance data from 350 nm to 1000 nm with spectral resolution of 1 nm. Due to high sun radiance levels we use a system of mirrors each reducing the signal to about 4%, while keeping the integration time short. The minimum integration time of 3 ms allows for detection of direct sunlight. The system developed is sensitive to small changes in the aerosol system, while showing a good detection limit even under low turbidity conditions. The system performance is demonstrated in field experiment conducted shortly after front passage when most of aerosol particles is effectively removed by rain.

Lunar sun-reflected light can be effectively measured through a low-light band or a day/night band (DNB) implemented on space-based optical sensors. Based on moonlight, nocturnal observations for artificial light sources at night can be achieved. However, to date, an open-sourced and mature Low-Light Radiative Transfer Model (LLRTM) for the further understanding of the radiative transfer problem at night is still unavailable. Therefore, this study develops a new LLRTM at night with the correction of the lunar and active surface light sources. First, the radiative transfer equations with an active surface light source are derived for the calculation based on the lunar spectral irradiance (LSI) model. The simulation from this new LLRTM shows a minimal bias when compared with the discrete ordinates radiative transfer (DISORT) model. The simulated results of radiance and reflectance at the top of the atmosphere (TOA) also show that the surface light source has a remarkable impact on the radiative transfer process. In contrast, the change in the lunar phase angle has minimal influence. Also, comparing with space-based DNB radiance observations, LLRTM shows the potential to simulate space-based low-light imager observations under an effective surface light source condition during the night.

Several light pollution indicators are commonly used to monitor the effects of the transition from outdoor lighting systems based on traditional gas-discharge lamps to solid-state light sources. In this work we analyze a subset of these indicators, including the artificial zenithal night sky brightness in the visual photopic and scotopic bands, the brightness in the specific photometric band of the widely used Sky Quality Meter (SQM), and the top-of-atmosphere radiance detected by the VIIRS-DNB radiometer onboard the satellite Suomi-NPP. Using a single-scattering approximation in a layered atmosphere we quantitatively show that, depending on the transition scenarios, these indicators may show different, even opposite behaviors. This is mainly due to the combined effects of the changes in the sources' spectra and angular radiation patterns, the wavelength-dependent atmospheric propagation processes and the differences in the detector spectral sensitivity bands. It is suggested that the possible presence of this differential behavior should be taken into account when evaluating light pollution indicator datasets for assessing the outcomes of public policy decisions regarding the upgrading of outdoor lighting systems.